Operations | Monitoring | ITSM | DevOps | Cloud

Apache Cassandra has long been favored by organizations dealing with large volumes of data that require distributed storage and processing capabilities. Its decentralized architecture and tunable consistency levels make it ideal for handling massive datasets across multiple nodes with minimal latency. On the other hand, Apache Spark excels in processing and analyzing data in-memory, making it an excellent complement to Cassandra for performing real-time analytics and batch processing tasks.

In the current digital space, businesses are constantly looking for solutions that can help them save time and money. One such solution is cloud-based receipt software. It provides a way for consumers to move away from paper receipts, but does it make sense for organizations wanting to modernize?

Smart devices have redefined how we experience road safety. Advances in technology have led to innovative solutions designed to monitor and improve driving behavior. These devices enhance safety and provide actionable insights for drivers and fleet managers. Understanding how these smart devices work is important for any driver looking to leverage technology for a safer driving experience.

We're happy to announce Raygun's new remote MCP server, giving AI tools direct access to live error data so they can investigate issues, surface root causes, and take action with real context, not guesses. It's been nearly a year since Anthropic released the Model Context Protocol (MCP), and a lot has changed in the AI space. Since then, almost all major players now support MCP, allowing them to tap into the massive and ever-expanding catalogue of MCP servers. When MCP first launched, we shipped our own Raygun MCP within 48 hours of the spec dropping, which was an early step toward giving LLMs visibility into Raygun data.